Pricing, context window, capabilities, and release date — pulled from each provider's public docs. Both are available via the same AIgateway OpenAI-compatible endpoint; flip the model string to switch.
Both models stream in parallel through your own AIgateway key. Tokens, latency, and cost update as they arrive.
| Qwen3-Embedding-0.6b qwen/qwen3-embedding-0.6b | Qwen3.8-27b qwen/qwen3.8-27b | |
|---|---|---|
| Provider | Alibaba Qwen | Alibaba Qwen |
| Family | Qwen | Qwen |
| Modality | embedding | text |
| Context window | — | 262,144 tok |
| Max output | — | 32,768 tok |
| Released | 2025-06-18 | 2026-08-17 |
| Input price | $0.012 /1M | $0.450 /1M |
| Output price | $0.0000 /1M | $3.20 /1M |
| Cache read | — | — |
| Tools | — | yes |
| Streaming | — | yes |
| Vision | — | yes |
| JSON mode | — | yes |
| Reasoning | — | yes |
| Prompt caching | — | — |
The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks.
Qwen 3.8 27B is a 27-billion-parameter instruction-tuned language model from Alibaba's Qwen family, designed for vision, efficient general-purpose text generation and agentic workloads.
# pip install aigateway-py openai
# aigateway-py: sub-accounts, evals, replays, jobs, webhook verify.
# openai SDK: chat/embeddings/images/audio — drop-in compat per our SDK's own guidance.
from openai import OpenAI
client = OpenAI(
base_url="https://api.aigateway.sh/v1",
api_key="sk-aig-...",
)
# Try Qwen3-Embedding-0.6b
client.chat.completions.create(
model="qwen/qwen3-embedding-0.6b",
messages=[{"role":"user","content":"hello"}],
)
# Try Qwen3.8-27b — same client, same key
client.chat.completions.create(
model="qwen/qwen3.8-27b",
messages=[{"role":"user","content":"hello"}],
)